In conventional methods of X-ray imaging, attenuation depends on the type of body tissue scanned and the average energy level of the X-ray beam. The average energy level of the X-ray beam may be adjusted via an X-ray tube's energy setting. An X-ray tube's energy setting is measured in kilovolts (kV).
Conventionally, computed tomography (CT) imaging may be performed using a single energy level (referred to as single energy CT imaging) or dual energy levels (referred to as dual energy imaging). Dual energy images may be acquired using two or more scans of different energies during a single procedure or using one or more energy sources.
In conventional single energy CT imaging, image data is obtained using a single energy value, for example, 120 kV. In conventional dual energy CT imaging, dual image data (e.g., two image data sets or two images) is obtained using two different energy levels (e.g., 80 kV and 140 kV). Dual image data may be obtained concurrently, simultaneously or sequentially. If two different energy levels are used to acquire dual energy images, each of the two sets of image data may have different attenuation characteristics. The difference in attenuation levels allows for classification of elemental chemical compositions of imaged tissues.
Different energy levels may also impact contrast resolution and/or noise characteristics of respective image data. For example, 80 kV image data may provide greater contrast resolution than 140 kV image data. But, the 80 kV image data may be noisier than the 140 kV image data. To exploit potential advantages of, for example, 80 kV image data and 140 kV, in conventional dual energy CT systems, the higher and lower image data may be combined into resultant image data using a linear mixing ratio.
In one example, a conventional linear mixing ratio may be 70/30. In this case, resultant image data may be obtained by blending 70% of a 140 kV image data with a 30% 80 kV image data. Methods for linear blending of image data are well-known in the art. Thus, a detailed discussion will be omitted for the sake of brevity.
In a more specific example, dual energy image data for a pancreas may have somewhat grainy 80 kV images lacking sharp contours, which may be shown in, for example, 120-140 kV images. However, the 80 kV images may have a better contrast resolution than the 120-140 kV images. The better contrast resolution may enable physicians to differentiate between tissues. Thus, in conventional methods of linear combining, benefits of the 80 kV image data and the 120-140 kV image data may be at least partially offset by the drawbacks (e.g., noise) due to the linear nature of the combination.
Conventional linear blending may also provide additional diagnostic information to a viewing physician. However, illustrating the additional diagnostic information to the physician may be potentially problematic because of the drawbacks of the linear combination.